A method for topic discovery through structural knowledge in an associative document tree building system includes inserting a set of documents into nodes of a document tree, extracting a tag set of tags from the set of documents and inserting each tag into a different node of a tag tree. The method also includes conducting a search engine query using the tags of the extracted tag set to produce a new set of documents and inserting the new set of documents into nodes of the document tree. The method yet further includes extracting a new tag set of tags from the new set of documents and inserting each tag of the new tag set into a different node of the tag tree. Finally, the method includes displaying at least a portion of each of the document tree and tag tree in a user interface displayed.
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1. A method for topic discovery through structural knowledge in an associative document tree building system, the method comprising: inserting a set of documents into nodes of a document tree in memory of a host computing system; extracting a tag set of tags from the set of documents and inserting each tag into a different node of a tag tree in the memory of the host computing system; conducting a search engine query through the host computing system using the tags of the extracted tag set to produce a new set of documents; inserting the new set of documents into nodes of the document tree; extracting a new tag set of tags from the new set of documents and inserting each of tag of the new tag set into a different node of the tag tree; and, displaying at least a portion of each of the document tree and tag tree in a user interface displayed by the host computing system.
A system for topic discovery builds associative document trees by inserting documents into nodes of a document tree. It extracts tags from the documents and inserts each tag into a separate node of a tag tree. Using these tags, a search engine query is performed to find new documents, which are then added to the document tree. New tags are extracted from these new documents and added to the tag tree. Finally, both the document tree and the tag tree are displayed in a user interface.
2. The method of claim 1 , wherein the insertion of the sets of documents into the document tree is limited by breadth constraints of the document tree.
The method for topic discovery described in claim 1 includes a document tree where the addition of document sets is constrained by the breadth of the document tree, meaning there's a limit to how many nodes can be added at each level. This prevents the tree from becoming too wide and unmanageable, maintaining a structured representation of the document relationships.
3. The method of claim 1 , wherein the insertion of the tag sets of tags into the tag tree is limited by breadth constraints of the tag tree.
The method for topic discovery described in claim 1 includes a tag tree where the addition of tag sets is constrained by the breadth of the tag tree, meaning there's a limit to how many nodes can be added at each level. This keeps the tag tree organized and prevents it from becoming overly complex, enabling efficient navigation and topic identification.
4. The method of claim 1 , wherein the conduct of the search engine query, the insertion of the new set of documents resulting from the search engine query, and the extraction and insertion of the new tag set of tags from the new set of documents into nodes of the tag tree repeats until a depth constraint for each of the trees is met.
The method for topic discovery described in claim 1 iteratively refines the document and tag trees. The process of querying the search engine, adding new documents, and extracting/inserting new tags repeats until a depth constraint is met for both trees. This depth constraint determines the maximum levels the trees can grow to, balancing thorough topic exploration with resource limitations and ensuring the trees remain manageable.
5. The method of claim 1 , wherein meta-data for a selected node of a corresponding tree in the user interface is displayed in the user interface.
The method for topic discovery described in claim 1 displays metadata for a selected node in either the document tree or the tag tree within the user interface. This metadata provides additional information about the selected document or tag, such as its source, creation date, or related keywords, enabling users to gain deeper insights into the discovered topics and their relationships.
6. A method for topic discovery through structural knowledge in an associative document tree building system, the method comprising: inserting tags of a tag set into nodes of a tag tree in memory of a host computing system; conducting a search engine query through the host computing system using the tags of the tag set to produce a set of documents and inserting each document in the set of documents into a corresponding node of a document tree in the memory of the host computing system; extracting a new tag set of tags from the set of documents and inserting each tag of the new tag set into a different node of the tag tree; conducting a new search engine query through the host computing system using the tags of the new tag set of tags to produce a new set of documents; inserting the new set of documents into respectively different nodes of the document tree; and, displaying at least a portion of each of the document tree and tag tree in a user interface displayed by the host computing system.
A system discovers topics by building associative trees. Initially, tags are placed into nodes of a tag tree. These tags are used in a search engine query to find documents, which are then placed into nodes of a document tree. New tags are extracted from these documents and inserted into the tag tree. Another search engine query is performed using these new tags to find more documents, which are then added to the document tree. Finally, both the document tree and tag tree are displayed in a user interface.
7. The method of claim 6 , wherein the insertion of the sets of documents into the document tree is limited by breadth constraints of the document tree.
The method for topic discovery described in claim 6 includes a document tree where adding document sets is restricted by the breadth of the document tree, limiting the number of nodes at each level. This ensures a manageable and structured representation of document relationships, preventing the tree from becoming excessively wide.
8. The method of claim 6 , wherein the insertion of the sets of tags into the tag tree is limited by breadth constraints of the tag tree.
The method for topic discovery described in claim 6 includes a tag tree where adding tag sets is limited by the breadth of the tag tree, restricting the number of nodes at each level. This organization helps maintain clarity and prevents the tag tree from becoming too complex for efficient topic identification.
9. The method of claim 6 , wherein the conduct of the search engine queries, the insertion of a new set of documents resulting from the search engine queries, and the extraction and insertion of new tag sets of tags from the new set of documents into nodes of the tag tree repeats until a depth constraint for each of the trees is met.
The method for topic discovery described in claim 6 iteratively refines the document and tag trees. The process involving search engine queries, inserting new documents, and extracting/inserting new tags repeats until a depth constraint is reached for both trees. This depth constraint limits how deep the trees can grow, balancing comprehensive exploration with resource limits to keep the trees manageable.
10. The method of claim 6 , wherein meta-data for a selected node of a corresponding tree in the user interface is displayed in the user interface.
The method for topic discovery described in claim 6 shows metadata for a chosen node in either the document tree or the tag tree within the user interface. This additional data provides information like the source or creation date of the selected document or tag, helping users better understand the discovered topics and their connections.
11. A computer program product for topic discovery through structural knowledge in an associative document tree building system, the computer program product comprising: a computer readable storage medium comprising a device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for inserting a set of documents into nodes of a document tree; computer readable program code for extracting a tag set of tags from the set of documents and inserting each tag into a different node of a tag tree; computer readable program code for conducting a search engine query using the tags of the extracted tag set to produce a new set of documents; computer readable program code for inserting the new set of documents into nodes of the document tree; computer readable program code for extracting a new tag set of tags from the new set of documents and inserting each of tag of the new tag set into a different node of the tag tree; and, computer readable program code for displaying at least a portion of each of the document tree and tag tree in a user interface.
A computer program product for topic discovery builds associative document trees. The program code inserts documents into nodes of a document tree, extracts tags and inserts them into a tag tree. It uses these tags to perform a search engine query for new documents, which are added to the document tree. New tags from the new documents are extracted and added to the tag tree. Finally, it displays both the document tree and tag tree in a user interface.
12. The computer program product of claim 11 , wherein the insertion of the sets of documents into the document tree is limited by breadth constraints of the document tree.
The computer program product from the previous topic discovery description includes a document tree where adding document sets is restricted by the breadth of the document tree, as described in claim 11, limiting the number of nodes at each level. This ensures the program builds a manageable and well-structured representation of document relationships within the document tree.
13. The computer program product of claim 11 , wherein the insertion of the tag sets of tags into the tag tree is limited by breadth constraints of the tag tree.
The computer program product from the previous topic discovery description includes a tag tree where adding tag sets is limited by the breadth of the tag tree, as described in claim 11, restricting the number of nodes at each level. This ensures the program keeps the tag tree organized and clear, aiding in efficient topic identification.
14. The computer program product of claim 11 , wherein the conduct of the search engine query, the insertion of the new set of documents resulting from the search engine query, and the extraction and insertion of the new tag set of tags from the new set of documents into nodes of the tag tree repeats until a depth constraint for each of the trees is met.
The computer program product from the previous topic discovery description iteratively refines the document and tag trees, as described in claim 11. The process of querying the search engine, inserting new documents, and extracting/inserting new tags repeats until a depth constraint is met for both trees. This depth constraint ensures that the growth of the trees is limited, balancing the thoroughness of topic exploration with resource constraints.
15. The computer program product of claim 11 , wherein meta-data for a selected node of a corresponding tree in the user interface is displayed in the user interface.
The computer program product from the previous topic discovery description displays metadata for a selected node in either the document tree or the tag tree within the user interface, as described in claim 11. This provides additional information about the documents or tags, helping users gain deeper insights into the discovered topics.
16. A computer program product for topic discovery through structural knowledge in an associative document tree building system, the computer program product comprising: a computer readable storage medium comprising a device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for inserting tags of a tag set into nodes of a tag tree; computer readable program code for conducting a search engine query using the tags of the tag set to produce a set of documents and inserting each document in the set of documents into a corresponding node of a document tree; computer readable program code for extracting a new tag set of tags from the set of documents and inserting each tag of the new tag set into a different node of the tag tree; computer readable program code for conducting a new search engine query using the tags of the new tag set of tags to produce a new set of documents; computer readable program code for inserting the new set of documents into respectively different nodes of the document tree; and, computer readable program code for displaying at least a portion of each of the document tree and tag tree in a user interface.
A computer program product for topic discovery constructs associative document trees. The program code initially places tags into the nodes of a tag tree. It then performs a search engine query using these tags to find related documents, which are then placed into nodes of a document tree. The program extracts new tags from these documents and inserts them into the tag tree. It repeats the process with a new search engine query using the new tags to find further documents, adding them to the document tree. Finally, both the document tree and tag tree are displayed in a user interface.
17. The computer program product of claim 16 , wherein the insertion of the sets of documents into the document tree is limited by breadth constraints of the document tree.
The computer program product from the previous topic discovery description features a document tree where the insertion of document sets is limited by breadth constraints of the document tree as described in claim 16. This ensures that the tree doesn't become excessively wide and remains manageable.
18. The computer program product of claim 16 , wherein the insertion of the sets of tags into the tag tree is limited by breadth constraints of the tag tree.
The computer program product from the previous topic discovery description features a tag tree where the insertion of tag sets is limited by breadth constraints of the tag tree as described in claim 16. This keeps the tag tree organized and prevents it from becoming overly complex.
19. The computer program product of claim 16 , wherein the conduct of the search engine queries, the insertion of a new set of documents resulting from the search engine queries, and the extraction and insertion of new tag sets of tags from the new set of documents into nodes of the tag tree repeats until a depth constraint for each of the trees is met.
The computer program product from the previous topic discovery description involves conducting search engine queries, inserting new documents resulting from the search engine queries, and extracting and inserting new tag sets of tags from the new set of documents into nodes of the tag tree as described in claim 16. This process repeats until a depth constraint for each of the trees is met, ensuring balanced exploration and resource use.
20. The computer program product of claim 16 , wherein meta-data for a selected node of a corresponding tree in the user interface is displayed in the user interface.
The computer program product from the previous topic discovery description includes the feature where meta-data for a selected node of a corresponding tree in the user interface is displayed in the user interface as described in claim 16. This provides users with detailed information for each node.
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October 8, 2012
August 22, 2017
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